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Social Network Data Analytics

  • Charu C. Aggarwal

Table of contents

  1. Front Matter
    Pages 1-1
  2. Mary McGlohon, Leman Akoglu, Christos Faloutsos
    Pages 17-42
  3. Purnamrita Sarkar, Andrew W. Moore
    Pages 43-77
  4. S. Parthasarathy, Y. Ruan, V. Satuluri
    Pages 79-113
  5. Smriti Bhagat, Graham Cormode, S. Muthukrishnan
    Pages 115-148
  6. Myra Spiliopoulou
    Pages 149-175
  7. Theodoros Lappas, Kun Liu, Evimaria Terzi
    Pages 215-241
  8. Mohammad Al Hasan, Mohammed J. Zaki
    Pages 243-275
  9. Elena Zheleva, Lise Getoor
    Pages 277-306
  10. Carlos D. Correa, Kwan-Liu Ma
    Pages 307-326
  11. Geoffrey Barbier, Huan Liu
    Pages 327-352
  12. Charu C. Aggarwal, Haixun Wang
    Pages 353-378
  13. Charu C. Aggarwal, Tarek Abdelzaher
    Pages 379-412
  14. Liangliang Cao, GuoJun Qi, Shen-Fu Tsai, Min-Hsuan Tsai, Andrey Del Pozo, Thomas S. Huang et al.
    Pages 413-445
  15. Manish Gupta, Rui Li, Zhijun Yin, Jiawei Han
    Pages 447-497
  16. Back Matter
    Pages 18-18

About this book

Introduction

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes.

Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book.

This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

Keywords

Fuzzy social networks Intelligent social network modeling Modularity of social network communities P2P infrastructure for social networks Preserving privacy in social networks Social network analysis Social networks Visualizing social networks Web mining techniques for social networks social network profile and policy social networks for semantic advertisement

Editors and affiliations

  • Charu C. Aggarwal
    • 1
  1. 1.Thomas J. Watson Research CenterIBMHawthorneUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-8462-3
  • Copyright Information Springer Science+Business Media, LLC 2011
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-1-4419-8461-6
  • Online ISBN 978-1-4419-8462-3
  • Buy this book on publisher's site
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